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» On the use of spiking neural network for EEG classification
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BC
2007
107views more  BC 2007»
13 years 8 months ago
Decoding spike train ensembles: tracking a moving stimulus
We consider the issue of how to read out the information from nonstationary spike train ensembles. Based on the theory of censored data in statistics, we propose a ‘censored’ m...
Enrico Rossoni, Jianfeng Feng
ICIC
2007
Springer
14 years 2 months ago
Edge Detection Based on Spiking Neural Network Model
Inspired by the behaviour of biological receptive fields and the human visual system, a network model based on spiking neurons is proposed to detect edges in a visual image. The st...
Qingxiang Wu, T. Martin McGinnity, Liam P. Maguire...
ICANN
2005
Springer
14 years 2 months ago
A Real-Time, FPGA Based, Biologically Plausible Neural Network Processor
Abstract. A real-time, large scale, leaky-integrate-and-fire neural network processor realized using FPGA is presented. This has been designed, as part of a collaborative project,...
Martin J. Pearson, Ian Gilhespy, Kevin N. Gurney, ...
NN
2008
Springer
150views Neural Networks» more  NN 2008»
13 years 8 months ago
Neural network based pattern matching and spike detection tools and services - in the CARMEN neuroinformatics project
In the study of information flow in the nervous system, component processes can be investigated using a range of electrophysiological and imaging techniques. Although data is diff...
Martyn Fletcher, Bojian Liang, Leslie Smith, Alast...
NIPS
2007
13 years 10 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...